RESEARCH PAPER
Multi-objective optimization design of rail grinding profile in Curve Section of Subway based on wear Evolution and representative worn profile
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1
East China Jiaotong University, China
2
Jiangxi Industrial Polytechnic College, China
3
Pingxiang University, China
These authors had equal contribution to this work
Submission date: 2024-04-22
Final revision date: 2024-05-26
Acceptance date: 2024-07-22
Online publication date: 2024-07-27
Publication date: 2024-07-27
Corresponding author
Jun Zhou
East China Jiaotong University, China
HIGHLIGHTS
- This study utilizes Dynamic Time Warping (DTW) to select a representative rail worn profile for optimization design from the rail worn profile.
- This paper proposes an optimization mathematical model that considers the evolution of wheel profile wear for design optimization.
- Adaptive weight adjustment factor coefficients are introduced to avoid the subjective influence of the designer’s experience.
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ABSTRACT
Curve rail grinding has always been one of the key points of subway maintenance and repair. The appropriate grinding can effectively reduce wear. A multi-objective optimization design method for grinding profiles in curved sections is proposed. Firstly, representative grinding profiles are selected as the initial population using the dynamic time regularization algorithm (DTW). Then, the optimal design range is determined based on wear characterization analysis, and mathematical expressions of wheel profiles are chosen as design variables to establish a parametric model. Next, the prediction model considering the evolution of wheel wear is incorporated into the multi-objective function, and objective function adaptive weight adjustment coefficient factors are introduced to establish the multi-objective optimization model for wheel profiles. The Latin hypercubic sampling method is employed to establish the RBF agent model for simulation calculation, and the optimization design of wheel profiles is carried out using the TS-NSGA-II multi-objective algorithm.